A statistical method for evaluating detection efficiency of lightning location network and its application

Abstract A statistical method for evaluating the detection efficiency (DE) of a lightning location network (LLN) has been proposed and examined. In the method, a LLN with a great number of sensors is grouped into sub-networks each with at least 3 sensors. The LLN covered area is divided into cells each with a small size (for instance 20 km × 20 km). The DE for a sensor in a sub-network at a cell is then estimated based on a comparison of the number of lightning strokes detected by at least 3 sensors with that detected by at least 2 sensors in the sub-network at the cell. The method was applied to a LLN in China, which consists of 25 sensors covering an area of about 1350 km × 1030 km. With historical data, the DE for all 25 sensors at different cells was estimated. Results show that the DE varies with different sensors at different distance and azimuth to the sensor, which may reflect the influence of the terrain, installation environment and sensor's parameter setting on the DE of a sensor. The DE of a sensor usually has a low value of 20–50% within 20 km of the sensor, and then gradually increases to a maximum value of 60–80% at 60–120 km, and then gets down to 20–30% at 220–240 km away. The overall DE of the LLN as a whole was also estimated, ranging from 60 to 90% for most of the inner area of the LLN.

[1]  M. Ishii,et al.  Seasonal variation of cloud-to-ground lightning flash characteristics in the coastal area of the Sea of Japan , 1989 .

[2]  K.L. Cummins,et al.  An Overview of Lightning Locating Systems: History, Techniques, and Data Uses, With an In-Depth Look at the U.S. NLDN , 2009, IEEE Transactions on Electromagnetic Compatibility.

[3]  Shuiming Chen,et al.  Evaluation of the Guang Dong lightning location system with transmission line fault data , 2002 .

[4]  Tengfei Zhang,et al.  Five-year study of cloud-to-ground lightning activity in Yunnan province, China , 2013 .

[5]  Dong Zheng,et al.  Performance Evaluation for a Lightning Location System Based on Observations of Artificially Triggered Lightning and Natural Lightning Flashes , 2012 .

[6]  E. Krider,et al.  Lightning Direction-Finding Systems for Forest Fire Detection , 1980 .

[7]  Herbert Songster,et al.  The East Coast Lightning Detection Network , 1986, IEEE Power Engineering Review.

[8]  W. David Rust,et al.  Site Errors and Detection Efficiency in a Magnetic Direction-Finder Network for Locating Lightning Strikes to Ground , 1986 .

[9]  Vladimir A. Rakov,et al.  Evaluation of U.S. National Lightning Detection Network performance characteristics using rocket-triggered lightning data acquired in 2004-2009 , 2011 .

[10]  Vladimir A. Rakov,et al.  An evaluation of the performance characteristics of the U.S. National Lightning Detection Network in Florida using rocket‐triggered lightning , 2005 .

[11]  Kenneth L. Cummins,et al.  National Lightning Detection Network (NLDN) performance in southern Arizona, Texas, and Oklahoma in 2003–2004 , 2007 .

[12]  Antti Mäkelä,et al.  The comparison of GLD360 and EUCLID lightning location systems in Europe , 2013 .

[13]  R. Orville,et al.  Lighting Ground Flash Density in the Contiguous United States: 1992–95 , 1991 .

[14]  Osmar Pinto,et al.  Improvements in the detection efficiency model for the Brazilian lightning detection network (BrasilDAT) , 2009 .

[15]  Shuiming Chen,et al.  A lightning location system in China: its performances and applications , 2002 .

[16]  Kenneth L. Cummins,et al.  A Combined TOA/MDF Technology Upgrade of the U.S. National Lightning Detection Network , 1998 .

[17]  P. Jamason,et al.  Performance evaluation of the U.S. National Lightning , 1998 .